HIRLAM/HARMONIE work on surface data assimilation and modelling

Transcription

1 HIRLAM/HARMONIE work on surface data assimilation and modelling Ekaterina Kourzeneva *, Laura Rontu, Trygve Aspelien, Maria Diez, Mariken Homleid, Kalle Eerola, Suleiman Mostamandi, Patrick Samuelsson, Stefan Gollvick, Bin Cheng, Homa Keyrollahpour, Yurii Batrak, Carl Fortelius, Timo Vihma, Tiina Kilpelainen, Nicolas Bauer, Margarita Shoulga

2 Contents Introduction HIRLAM/HARMONIE Operational status Ongoing and planned R&D Technical developments Soil and vegetation Snow Sea ice Lakes Urban Surface layer Orography Physiography

3 Introduction: HIRLAM... HARMONIE HIRLAM - operational limited area model: , v.7.4 HARMONIE - pre-operational local NWP system based on ALADIN-AROME used and developed within HIRLAM consortium since 2005

4 Operational status HIRLAM v.7.4 DA: span in hor: OI for screen level temperature and relative humidity (anisotrophy due to land-sea and orography), SST and SWE in ver: OI to get soil temperature and soil moisture obs: SYNOP, ECMWF SST (OSTIA), LST from SYKE

5 Operational status HIRLAM v.7.4 physiography: GLCC+CORINE, FAO soil map, GTOPO, lake depth database surface layer fluxes: Louis formulation surface schemes: 5 tiles water(sea/lakes), sea ice, bare soil, low vegetation, high vegetation; land tiles may be covered by snow ISBA 2L, newsnow scheme (1.5 layer in snow, snow on high vegetation), FLake, orographic radiation effects

6 Operational status HARMONIE-36 DA: CANARI + OI_MAIN in hor: OI for screen level temperature, relative humidity and SWE, bilinear interpolation for SST in ver: OI to get soil temperature and soil moisture obs: SINOP, OSTIA

7 Operational status HARMONIE-36 physiography: ECOCLIMAP2, FAO soil map, GTOPO surface layer fluxes: canopy surface schemes: SURFEX6.2 3 tiles water, urban, nature; nature tile may be covered by snow ISBA 3L, 1 layer in snow

8 Technical developments SODA: SURFEX Offline Data Assimilation off-line parallel system with CANARI and SURFEX/VARASIM

9 Soil and vegetation Testing of soil moisture analysis with EKF Contribution from NILU: EnEKF, particle filter, ASCAT and SMOS data EURO4M

10 Snow, DA Obs: Precipitation stations Candidates of satellite snow extend data: - CryoRisk satellite data, 15 km resolution - NOAA/NESDIS data - LANDSAF data

11 Snow, DA Satellite SWE obs: GLOBSNOW Verification against independent SYNOPs and careful analysis show that GLOBSNOW data are not applicable in the present form. Modification of the algorithm is needed to make first steps forward to assimilate brightness temperatures

12 Snow, DA in ver.: to assimilate snow depth with EKF using experience of R. Essery with JULES rms error mm 0.14 m 0.05 m 1.15 º C 0.79 º C

13 Snow modelling MEB: Multi Energy Balance scheme T g EBA D95 T 3-L T n g CRO No explicit canopy vegetation energy balance (temperature)!

14 Snow modelling Snow well below the canopy Snow partly buries the canopy Snow buries the canopy T v T c T v T c T v T c T n T n T n T g T g T g MEB is designed to work with snow schemes 3-L and CRO (requires separate snow energy balance) soil schemes 2-L & 3-L (force restore) and DIF (diffusion)

15 Snow modelling MEB:

16 Sea ice ECMWF SST optimally interpolated Detect ice if SST < K HIGHTSI: High Resolution Thermodynamic Ice Model First step: simple 2L HIRLAM sea ice scheme

17 Lakes DA of LST in hor: experiments to assimilate MODIS data with currently used OI (developed for SST)

18 Lakes DA of LST in ver: EKF to assimilate in-situ LST measurements operational obs. from Finnish Environmental Institute (SYKE) 27 lakes in Finland

19 Lakes DA of LST in ver: EKF for mixed and non-mixed regime for ice-non-ice period Lake Inari

20 Lakes DA of LST in ver: EKF: use MODIS data, include into SODA include into HARMONIE Lake Tuusula

21 Lakes Errors in spring! Lake Amisk, Canada Improved lake model climatology Intensive experiments to find reasons: 30 lon, 60 lat, 10m - forcing from GLWD, NCEP, GDAS - albedo formulations - numerical schemes - snow scheme on/off

22 Lakes Improved lake model climatology The best configuration was found Lake Manasbal, India New climatology was compiled and verifyed against in-situ obs Lake Ennady, Canada

23 Urban High Resolution Town Description Testing of TEB

24 Surface layer Stable boundary layer problem GABLS4 GEWEX Atmosheric Boundary Layer Study

25 Orography Parametrisation of orographic radiation effects in SURFEX S dr S df F F F S df F S df F F

26 Orography very fine resolution data

27 Orography very fine resolution data

28 Orography very fine resolution data

29 Physiography New high resolution data on percentage of sand and clay: to test over Nordic domain and to use in HARMONIE To compare ECOCLIMAP with local datasets: glaciers, permanent snow, etc.

30 Physiography GLDB v.2 Global Lake Database 141 region Typical lake depth depending on the geological origin of lakes in the region

31 Physiography Statistical analysis for each region GLDB v.2 Typical lake depth

32 Thank you!